Abstract

Knowledge of phytoplankton community structures is important to the understanding of various marine biogeochemical processes and ecosystem. Fluorescence excitation spectra (F(λ)) provide great potential for studying phytoplankton communities because their spectral variability depends on changes in the pigment compositions related to distinct phytoplankton groups. Commercial spectrofluorometers have been developed to analyze phytoplankton communities by measuring the field F(λ), but estimations using the default methods are not always accurate because of their strong dependence on norm spectra, which are obtained by culturing pure algae of a given group and are assumed to be constant. In this study, we proposed a novel approach for estimating the chlorophyll a (Chl a) fractions of brown algae, cyanobacteria, green algae and cryptophytes based on a data set collected in the East China Sea (ECS) and the Tsushima Strait (TS), with concurrent measurements of in vivo F(λ) and phytoplankton communities derived from pigments analysis. The new approach blends various statistical features by computing the band ratios and continuum-removed spectra of F(λ) without requiring a priori knowledge of the norm spectra. The model evaluations indicate that our approach yields good estimations of the Chl a fractions, with root-mean-square errors of 0.117, 0.078, 0.072 and 0.060 for brown algae, cyanobacteria, green algae and cryptophytes, respectively. The statistical analysis shows that the models are generally robust to uncertainty in F(λ). We recommend using a site-specific model for more accurate estimations. To develop a site-specific model in the ECS and TS, approximately 26 samples are sufficient for using our approach, but this conclusion needs to be validated in additional regions. Overall, our approach provides a useful technical basis for estimating phytoplankton communities from measurements of F(λ).

© 2016 Optical Society of America

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References

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2016 (1)

J. Harrison, T. E. Howell, S. B. Watson, and R. E. Smith, “Improved estimates of phytoplankton community composition based on in situ spectral fluorescence: use of ordination and field-derived norm spectra for the bbe FluoroProbe,” Can. J. Fish. Aquat. Sci. 73(10), 1472–1482 (2016).
[Crossref]

2015 (4)

A. Bracher, M. Taylor, B. Taylor, T. Dinter, R. Röttgers, and F. Steinmetz, “Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of phytoplankton pigments concentrations,” Ocean Sci. 11(1), 139–158 (2015).
[Crossref]

S. Wang, J. Ishizaka, T. Hirawake, Y. Watanabe, Y. Zhu, M. Hayashi, and S. Yoo, “Remote estimation of phytoplankton size fractions using the spectral shape of light absorption,” Opt. Express 23(8), 10301–10318 (2015).
[Crossref] [PubMed]

V. S. Kuwahara and S. C. Y. Leong, “Spectral fluorometric characterization of phytoplankton types in the tropical coastal waters of Singapore,” J. Exp. Mar. Biol. Ecol. 466, 1–8 (2015).
[Crossref]

N. Escoffier, C. Bernard, S. Hamlaoui, A. Groleau, and A. Catherine, “Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state,” J. Plankton Res. 37(1), 233–247 (2015).
[Crossref]

2014 (4)

S. Wang, J. Ishizaka, H. Yamaguchi, S. Tripathy, M. Hayashi, Y. Xu, Y. Mino, T. Matsuno, Y. Watanabe, and S. Yoo, “Influence of the Changjiang River on the light absorption properties of phytoplankton from the East China Sea,” Biogeosciences 11(7), 1759–1773 (2014).
[Crossref]

X. Chen, R. Su, Y. Bai, X. Shi, and R. Yang, “Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX,” Acta Oceanol. Sin. 33(12), 192–205 (2014).
[Crossref]

S. Sathyendranath, J. Aiken, S. Barlow, and H. Bouman, “Phytoplankton functional types from Space,” Rep. Internat. Ocean-Col. Coordin. Grp. (IOCCG) 15, 1–156 (2014).

S. A. Kring, S. E. Figary, G. L. Boyer, S. B. Watson, and M. R. Twiss, “Rapid in situ measures of phytoplankton communities using the bbe FluoroProbe: evaluation of spectral calibration, instrument intercompatibility, and performance range,” Can. J. Fish. Aquat. Sci. 71(7), 1087–1095 (2014).
[Crossref]

2013 (2)

Z. Li, L. Li, K. Song, and N. Cassar, “Estimation of phytoplankton size fractions based on spectral features of remote sensing ocean color data,” J.Geophys. Res.: Oceans 118(3), 1445–1458 (2013).
[Crossref]

H. Hofmann and F. Peeters, “In-situ optical and acoustical measurements of the buoyant cyanobacterium p. Rubescens: spatial and temporal distribution patterns,” PLoS One 8(11), e80913 (2013).
[Crossref] [PubMed]

2012 (7)

A. Catherine, N. Escoffier, A. Belhocine, A. B. Nasri, S. Hamlaoui, C. Yéprémian, C. Bernard, and M. Troussellier, “On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs,” Water Res. 46(6), 1771–1784 (2012).
[Crossref] [PubMed]

E. Houliez, F. Lizon, M. Thyssen, L. F. Artigas, and F. G. Schmitt, “Spectral fluorometric characterization of Haptophyte dynamics using the FluoroProbe: an application in the eastern English Channel for monitoring Phaeocystis globosa,” J. Plankton Res. 34(2), 136–151 (2012).
[Crossref]

X. Liu, B. Huang, Z. Liu, L. Wang, H. Wei, C. Li, and Q. Huang, “High-resolution phytoplankton diel variations in the summer stratified central Yellow Sea,” J. Oceanogr. 68(6), 913–927 (2012).
[Crossref]

H. Yamaguchi, H.-C. Kim, Y. B. Son, S. W. Kim, K. Okamura, Y. Kiyomoto, and J. Ishizaka, “Seasonal and summer interannual variations of SeaWiFS chlorophyll a in the Yellow Sea and East China Sea,” Prog. Oceanogr. 105, 22–29 (2012).
[Crossref]

S. E. Craig, C. T. Jones, W. K. W. Li, G. Lazin, E. Horne, C. Caverhill, and J. J. Cullen, “Deriving optical metrics of coastal phytoplankton biomass from ocean colour,” Remote Sens. Environ. 119, 72–83 (2012).
[Crossref]

R. Alexander, P. Gikuma-Njuru, and J. Imberger, “Identifying spatial structure in phytoplankton communities using multi‐wavelength fluorescence spectral data and principal component analysis,” Limnol. Oceanogr. Methods 10(6), 402–415 (2012).
[Crossref]

S. R. Rogers, T. Webster, W. Livingstone, and N. J. O’Driscoll, “Airborne Laser-Induced Fluorescence (LIF) Light Detection and Ranging (LiDAR) for the Quantification of Dissolved Organic Matter Concentration in Natural Waters,” Estuaries Coasts 35(4), 959–975 (2012).
[Crossref]

2011 (2)

J. R. Moisan, T. A. H. Moisan, and M. A. Linkswiler, “An inverse modeling approach to estimating phytoplankton pigment concentrations from phytoplankton absorption spectra,” J. Geophys. Res. 116(C9), C09018 (2011).
[Crossref]

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
[Crossref]

2010 (2)

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Modell. 221(11), 1472–1483 (2010).
[Crossref]

S. W. Wright, R. L. van den Enden, I. Pearce, A. T. Davidson, F. J. Scott, and K. J. Westwood, “Phytoplankton community structure and stocks in the Southern Ocean (30–80 E) determined by CHEMTAX analysis of HPLC pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 57(9-10), 758–778 (2010).
[Crossref]

2009 (2)

Z.-Y. Zhu, W.-M. Ng, S.-M. Liu, J. Zhang, J.-C. Chen, and Y. Wu, “Estuarine phytoplankton dynamics and shift of limiting factors: A study in the Changjiang (Yangtze River) Estuary and adjacent area,” Estuar. Coast. Shelf Sci. 84(3), 393–401 (2009).
[Crossref]

J. E. van Beusekom, D. Mengedoht, C. B. Augustin, M. Schilling, and M. Boersma, “Phytoplankton, protozooplankton and nutrient dynamics in the Bornholm Basin (Baltic Sea) in 2002–2003 during the German GLOBEC Project,” Int. J. Earth Sci. 98 (2), 251–260 (2009).
[Crossref]

2008 (2)

A. Nair, S. Sathyendranath, T. Platt, J. Morales, V. Stuart, M.-H. Forget, E. Devred, and H. Bouman, “Remote sensing of phytoplankton functional types,” Remote Sens. Environ. 112(8), 3366–3375 (2008).
[Crossref]

M. Zhou, Z. Shen, and R. Yu, “Responses of a coastal phytoplankton community to increased nutrient input from the Changjiang (Yangtze) River,” Cont. Shelf Res. 28(12), 1483–1489 (2008).
[Crossref]

2007 (3)

M. Latasa, “Improving estimations of phytoplankton class abundances using CHEMTAX,” Mar. Ecol. Prog. Ser. 329, 13–21 (2007).
[Crossref]

G. Johnsen and E. Sakshaug, “Biooptical characteristics of PSII and PSI in 33 species (13 pigment groups) of marine phytoplankton, and the relevance for pulse-amplitude-modulated and fast-repetition-rate fluorometry1,” J. Phycol. 43(6), 1236–1251 (2007).
[Crossref]

A. Bricaud, C. Mejia, D. Blondeau-Patissier, H. Claustre, M. Crepon, and S. Thiria, “Retrieval of pigment concentrations and size structure of algal populations from their absorption spectra using multilayered perceptrons,” Appl. Opt. 46(8), 1251–1260 (2007).
[Crossref] [PubMed]

2005 (3)

J. Gregor, R. Geriš, B. Maršálek, J. Heteša, and P. Marvan, “In situ quantification of phytoplankton in reservoirs using a submersible spectrofluorometer,” Hydrobiologia 548(1), 141–151 (2005).
[Crossref]

T. Kameda and J. Ishizaka, “Size-fractionated primary production estimated by a two-phytoplankton community model applicable to ocean color remote sensing,” J. Oceanogr. 61(4), 663–672 (2005).
[Crossref]

J. H. See, L. Campbell, T. L. Richardson, J. L. Pinckney, R. Shen, and N. L. Guinasso, “Combining new technologies for determination of phytoplankton community structure in the Northern Gulf of Mexico 1,” J. Phycol. 41(2), 305–310 (2005).
[Crossref]

2004 (3)

F. van der Meer, “Analysis of spectral absorption features in hyperspectral imagery,” Int. J. Appl. Earth Obs. Geoinf. 5(1), 55–68 (2004).
[Crossref]

A. Bricaud, H. Claustre, J. Ras, and K. Oubelkheir, “Natural variability of phytoplanktonic absorption in oceanic waters: Influence of the size structure of algal populations,” J. Geophys. Res.: Oceans 109(C11), 1978–2012 (2004).
[Crossref]

D. L. Rudnick, R. E. Davis, C. C. Eriksen, D. M. Fratantoni, and M. J. Perry, “Underwater gliders for ocean research,” Mar. Technol. Soc. J. 38(2), 73–84 (2004).
[Crossref]

2003 (1)

K. Furuya, M. Hayashi, Y. Yabushita, and A. Ishikawa, “Phytoplankton dynamics in the East China Sea in spring and summer as revealed by HPLC-derived pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 50(2), 367–387 (2003).
[Crossref]

2002 (4)

A. Isobe, M. Ando, T. Watanabe, T. Senjyu, S. Sugihara, and A. Manda, “Freshwater and temperature transports through the Tsushima‐Korea Straits,” J. Geophys. Res.: Oceans 107(C7), 3065 (2002).
[Crossref]

M. Beutler, K. H. Wiltshire, B. Meyer, C. Moldaenke, C. Lüring, M. Meyerhöfer, U.-P. Hansen, and H. Dau, “A fluorometric method for the differentiation of algal populations in vivo and in situ,” Photosynth. Res. 72(1), 39–53 (2002).
[Crossref] [PubMed]

C. Leboulanger, U. Dorigo, S. Jacquet, B. Le Berre, G. Paolini, and J.-F. Humbert, “Application of a submersible spectrofluorometer for rapid monitoring of freshwater cyanobacterial blooms: a case study,” Aquat. Microb. Ecol. 30, 83–89 (2002).
[Crossref]

A. M. Ciotti, M. R. Lewis, and J. J. Cullen, “Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient,” Limnol. Oceanogr. 47(2), 404–417 (2002).
[Crossref]

2001 (1)

L. Van Heukelem and C. S. Thomas, “Computer-assisted high-performance liquid chromatography method development with applications to the isolation and analysis of phytoplankton pigments,” J. Chromatogr. A 910(1), 31–49 (2001).
[Crossref] [PubMed]

1998 (1)

C. B. Field, M. J. Behrenfeld, J. T. Randerson, and P. Falkowski, “Primary production of the biosphere: integrating terrestrial and oceanic components,” Science 281(5374), 237–240 (1998).
[Crossref] [PubMed]

1996 (2)

M. Mackey, D. Mackey, H. Higgins, and S. Wright, “CHEMTAX a program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton,” Mar. Ecol. Prog. Ser. 144, 265–283 (1996).
[Crossref]

G.-C. Gong, Y.-L. Lee Chen, and K.-K. Liu, “Chemical hydrography and chlorophyll a distribution in the East China Sea in summer: implications in nutrient dynamics,” Cont. Shelf Res. 16(12), 1561–1590 (1996).
[Crossref]

1995 (2)

A. Longhurst, S. Sathyendranath, T. Platt, and C. Caverhill, “An estimate of global primary production in the ocean from satellite radiometer data,” J. Plankton Res. 17(6), 1245–1271 (1995).
[Crossref]

D. M. Nelson, P. Tréguer, M. A. Brzezinski, A. Leynaert, and B. Quéguiner, “Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation,” Global Biogeochem. Cycles 9(3), 359–372 (1995).
[Crossref]

1986 (1)

C.-F. J. Wu, “Jackknife, bootstrap and other resampling methods in regression analysis,” Ann. Stat. 14(4), 1261–1295 (1986).
[Crossref]

1966 (1)

C. J. Lorenzen, “A method for the continuous measurement of in vivo chlorophyll concentration,” Deep Sea Res. Oceanogr. Abstr. 13(2), 223–227 (1966).
[Crossref]

1944 (1)

J. Berkson, “Application of the logistic function to bio-assay,” J. Am. Stat. Assoc. 39, 357–365 (1944).

Aiken, J.

S. Sathyendranath, J. Aiken, S. Barlow, and H. Bouman, “Phytoplankton functional types from Space,” Rep. Internat. Ocean-Col. Coordin. Grp. (IOCCG) 15, 1–156 (2014).

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
[Crossref]

Alexander, R.

R. Alexander, P. Gikuma-Njuru, and J. Imberger, “Identifying spatial structure in phytoplankton communities using multi‐wavelength fluorescence spectral data and principal component analysis,” Limnol. Oceanogr. Methods 10(6), 402–415 (2012).
[Crossref]

Ando, M.

A. Isobe, M. Ando, T. Watanabe, T. Senjyu, S. Sugihara, and A. Manda, “Freshwater and temperature transports through the Tsushima‐Korea Straits,” J. Geophys. Res.: Oceans 107(C7), 3065 (2002).
[Crossref]

Artigas, L. F.

E. Houliez, F. Lizon, M. Thyssen, L. F. Artigas, and F. G. Schmitt, “Spectral fluorometric characterization of Haptophyte dynamics using the FluoroProbe: an application in the eastern English Channel for monitoring Phaeocystis globosa,” J. Plankton Res. 34(2), 136–151 (2012).
[Crossref]

Augustin, C. B.

J. E. van Beusekom, D. Mengedoht, C. B. Augustin, M. Schilling, and M. Boersma, “Phytoplankton, protozooplankton and nutrient dynamics in the Bornholm Basin (Baltic Sea) in 2002–2003 during the German GLOBEC Project,” Int. J. Earth Sci. 98 (2), 251–260 (2009).
[Crossref]

Bai, Y.

X. Chen, R. Su, Y. Bai, X. Shi, and R. Yang, “Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX,” Acta Oceanol. Sin. 33(12), 192–205 (2014).
[Crossref]

Barciela, R. M.

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Modell. 221(11), 1472–1483 (2010).
[Crossref]

Barlow, R.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
[Crossref]

Barlow, S.

S. Sathyendranath, J. Aiken, S. Barlow, and H. Bouman, “Phytoplankton functional types from Space,” Rep. Internat. Ocean-Col. Coordin. Grp. (IOCCG) 15, 1–156 (2014).

Behrenfeld, M. J.

C. B. Field, M. J. Behrenfeld, J. T. Randerson, and P. Falkowski, “Primary production of the biosphere: integrating terrestrial and oceanic components,” Science 281(5374), 237–240 (1998).
[Crossref] [PubMed]

Belhocine, A.

A. Catherine, N. Escoffier, A. Belhocine, A. B. Nasri, S. Hamlaoui, C. Yéprémian, C. Bernard, and M. Troussellier, “On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs,” Water Res. 46(6), 1771–1784 (2012).
[Crossref] [PubMed]

Berkson, J.

J. Berkson, “Application of the logistic function to bio-assay,” J. Am. Stat. Assoc. 39, 357–365 (1944).

Bernard, C.

N. Escoffier, C. Bernard, S. Hamlaoui, A. Groleau, and A. Catherine, “Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state,” J. Plankton Res. 37(1), 233–247 (2015).
[Crossref]

A. Catherine, N. Escoffier, A. Belhocine, A. B. Nasri, S. Hamlaoui, C. Yéprémian, C. Bernard, and M. Troussellier, “On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs,” Water Res. 46(6), 1771–1784 (2012).
[Crossref] [PubMed]

Beutler, M.

M. Beutler, K. H. Wiltshire, B. Meyer, C. Moldaenke, C. Lüring, M. Meyerhöfer, U.-P. Hansen, and H. Dau, “A fluorometric method for the differentiation of algal populations in vivo and in situ,” Photosynth. Res. 72(1), 39–53 (2002).
[Crossref] [PubMed]

Blondeau-Patissier, D.

Boersma, M.

J. E. van Beusekom, D. Mengedoht, C. B. Augustin, M. Schilling, and M. Boersma, “Phytoplankton, protozooplankton and nutrient dynamics in the Bornholm Basin (Baltic Sea) in 2002–2003 during the German GLOBEC Project,” Int. J. Earth Sci. 98 (2), 251–260 (2009).
[Crossref]

Bouman, H.

S. Sathyendranath, J. Aiken, S. Barlow, and H. Bouman, “Phytoplankton functional types from Space,” Rep. Internat. Ocean-Col. Coordin. Grp. (IOCCG) 15, 1–156 (2014).

A. Nair, S. Sathyendranath, T. Platt, J. Morales, V. Stuart, M.-H. Forget, E. Devred, and H. Bouman, “Remote sensing of phytoplankton functional types,” Remote Sens. Environ. 112(8), 3366–3375 (2008).
[Crossref]

Boyer, G. L.

S. A. Kring, S. E. Figary, G. L. Boyer, S. B. Watson, and M. R. Twiss, “Rapid in situ measures of phytoplankton communities using the bbe FluoroProbe: evaluation of spectral calibration, instrument intercompatibility, and performance range,” Can. J. Fish. Aquat. Sci. 71(7), 1087–1095 (2014).
[Crossref]

Bracher, A.

A. Bracher, M. Taylor, B. Taylor, T. Dinter, R. Röttgers, and F. Steinmetz, “Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of phytoplankton pigments concentrations,” Ocean Sci. 11(1), 139–158 (2015).
[Crossref]

Brewin, R. J. W.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
[Crossref]

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Modell. 221(11), 1472–1483 (2010).
[Crossref]

Bricaud, A.

A. Bricaud, C. Mejia, D. Blondeau-Patissier, H. Claustre, M. Crepon, and S. Thiria, “Retrieval of pigment concentrations and size structure of algal populations from their absorption spectra using multilayered perceptrons,” Appl. Opt. 46(8), 1251–1260 (2007).
[Crossref] [PubMed]

A. Bricaud, H. Claustre, J. Ras, and K. Oubelkheir, “Natural variability of phytoplanktonic absorption in oceanic waters: Influence of the size structure of algal populations,” J. Geophys. Res.: Oceans 109(C11), 1978–2012 (2004).
[Crossref]

Brzezinski, M. A.

D. M. Nelson, P. Tréguer, M. A. Brzezinski, A. Leynaert, and B. Quéguiner, “Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation,” Global Biogeochem. Cycles 9(3), 359–372 (1995).
[Crossref]

Campbell, L.

J. H. See, L. Campbell, T. L. Richardson, J. L. Pinckney, R. Shen, and N. L. Guinasso, “Combining new technologies for determination of phytoplankton community structure in the Northern Gulf of Mexico 1,” J. Phycol. 41(2), 305–310 (2005).
[Crossref]

Cassar, N.

Z. Li, L. Li, K. Song, and N. Cassar, “Estimation of phytoplankton size fractions based on spectral features of remote sensing ocean color data,” J.Geophys. Res.: Oceans 118(3), 1445–1458 (2013).
[Crossref]

Catherine, A.

N. Escoffier, C. Bernard, S. Hamlaoui, A. Groleau, and A. Catherine, “Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state,” J. Plankton Res. 37(1), 233–247 (2015).
[Crossref]

A. Catherine, N. Escoffier, A. Belhocine, A. B. Nasri, S. Hamlaoui, C. Yéprémian, C. Bernard, and M. Troussellier, “On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs,” Water Res. 46(6), 1771–1784 (2012).
[Crossref] [PubMed]

Caverhill, C.

S. E. Craig, C. T. Jones, W. K. W. Li, G. Lazin, E. Horne, C. Caverhill, and J. J. Cullen, “Deriving optical metrics of coastal phytoplankton biomass from ocean colour,” Remote Sens. Environ. 119, 72–83 (2012).
[Crossref]

A. Longhurst, S. Sathyendranath, T. Platt, and C. Caverhill, “An estimate of global primary production in the ocean from satellite radiometer data,” J. Plankton Res. 17(6), 1245–1271 (1995).
[Crossref]

Chen, J.-C.

Z.-Y. Zhu, W.-M. Ng, S.-M. Liu, J. Zhang, J.-C. Chen, and Y. Wu, “Estuarine phytoplankton dynamics and shift of limiting factors: A study in the Changjiang (Yangtze River) Estuary and adjacent area,” Estuar. Coast. Shelf Sci. 84(3), 393–401 (2009).
[Crossref]

Chen, X.

X. Chen, R. Su, Y. Bai, X. Shi, and R. Yang, “Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX,” Acta Oceanol. Sin. 33(12), 192–205 (2014).
[Crossref]

Ciotti, A. M.

A. M. Ciotti, M. R. Lewis, and J. J. Cullen, “Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient,” Limnol. Oceanogr. 47(2), 404–417 (2002).
[Crossref]

Claustre, H.

A. Bricaud, C. Mejia, D. Blondeau-Patissier, H. Claustre, M. Crepon, and S. Thiria, “Retrieval of pigment concentrations and size structure of algal populations from their absorption spectra using multilayered perceptrons,” Appl. Opt. 46(8), 1251–1260 (2007).
[Crossref] [PubMed]

A. Bricaud, H. Claustre, J. Ras, and K. Oubelkheir, “Natural variability of phytoplanktonic absorption in oceanic waters: Influence of the size structure of algal populations,” J. Geophys. Res.: Oceans 109(C11), 1978–2012 (2004).
[Crossref]

Craig, S. E.

S. E. Craig, C. T. Jones, W. K. W. Li, G. Lazin, E. Horne, C. Caverhill, and J. J. Cullen, “Deriving optical metrics of coastal phytoplankton biomass from ocean colour,” Remote Sens. Environ. 119, 72–83 (2012).
[Crossref]

Crepon, M.

Cullen, J. J.

S. E. Craig, C. T. Jones, W. K. W. Li, G. Lazin, E. Horne, C. Caverhill, and J. J. Cullen, “Deriving optical metrics of coastal phytoplankton biomass from ocean colour,” Remote Sens. Environ. 119, 72–83 (2012).
[Crossref]

A. M. Ciotti, M. R. Lewis, and J. J. Cullen, “Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient,” Limnol. Oceanogr. 47(2), 404–417 (2002).
[Crossref]

Dau, H.

M. Beutler, K. H. Wiltshire, B. Meyer, C. Moldaenke, C. Lüring, M. Meyerhöfer, U.-P. Hansen, and H. Dau, “A fluorometric method for the differentiation of algal populations in vivo and in situ,” Photosynth. Res. 72(1), 39–53 (2002).
[Crossref] [PubMed]

Davidson, A. T.

S. W. Wright, R. L. van den Enden, I. Pearce, A. T. Davidson, F. J. Scott, and K. J. Westwood, “Phytoplankton community structure and stocks in the Southern Ocean (30–80 E) determined by CHEMTAX analysis of HPLC pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 57(9-10), 758–778 (2010).
[Crossref]

Davis, R. E.

D. L. Rudnick, R. E. Davis, C. C. Eriksen, D. M. Fratantoni, and M. J. Perry, “Underwater gliders for ocean research,” Mar. Technol. Soc. J. 38(2), 73–84 (2004).
[Crossref]

Devred, E.

A. Nair, S. Sathyendranath, T. Platt, J. Morales, V. Stuart, M.-H. Forget, E. Devred, and H. Bouman, “Remote sensing of phytoplankton functional types,” Remote Sens. Environ. 112(8), 3366–3375 (2008).
[Crossref]

Dinter, T.

A. Bracher, M. Taylor, B. Taylor, T. Dinter, R. Röttgers, and F. Steinmetz, “Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of phytoplankton pigments concentrations,” Ocean Sci. 11(1), 139–158 (2015).
[Crossref]

Dorigo, U.

C. Leboulanger, U. Dorigo, S. Jacquet, B. Le Berre, G. Paolini, and J.-F. Humbert, “Application of a submersible spectrofluorometer for rapid monitoring of freshwater cyanobacterial blooms: a case study,” Aquat. Microb. Ecol. 30, 83–89 (2002).
[Crossref]

Eriksen, C. C.

D. L. Rudnick, R. E. Davis, C. C. Eriksen, D. M. Fratantoni, and M. J. Perry, “Underwater gliders for ocean research,” Mar. Technol. Soc. J. 38(2), 73–84 (2004).
[Crossref]

Escoffier, N.

N. Escoffier, C. Bernard, S. Hamlaoui, A. Groleau, and A. Catherine, “Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state,” J. Plankton Res. 37(1), 233–247 (2015).
[Crossref]

A. Catherine, N. Escoffier, A. Belhocine, A. B. Nasri, S. Hamlaoui, C. Yéprémian, C. Bernard, and M. Troussellier, “On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs,” Water Res. 46(6), 1771–1784 (2012).
[Crossref] [PubMed]

Falkowski, P.

C. B. Field, M. J. Behrenfeld, J. T. Randerson, and P. Falkowski, “Primary production of the biosphere: integrating terrestrial and oceanic components,” Science 281(5374), 237–240 (1998).
[Crossref] [PubMed]

Field, C. B.

C. B. Field, M. J. Behrenfeld, J. T. Randerson, and P. Falkowski, “Primary production of the biosphere: integrating terrestrial and oceanic components,” Science 281(5374), 237–240 (1998).
[Crossref] [PubMed]

Figary, S. E.

S. A. Kring, S. E. Figary, G. L. Boyer, S. B. Watson, and M. R. Twiss, “Rapid in situ measures of phytoplankton communities using the bbe FluoroProbe: evaluation of spectral calibration, instrument intercompatibility, and performance range,” Can. J. Fish. Aquat. Sci. 71(7), 1087–1095 (2014).
[Crossref]

Forget, M.-H.

A. Nair, S. Sathyendranath, T. Platt, J. Morales, V. Stuart, M.-H. Forget, E. Devred, and H. Bouman, “Remote sensing of phytoplankton functional types,” Remote Sens. Environ. 112(8), 3366–3375 (2008).
[Crossref]

Fratantoni, D. M.

D. L. Rudnick, R. E. Davis, C. C. Eriksen, D. M. Fratantoni, and M. J. Perry, “Underwater gliders for ocean research,” Mar. Technol. Soc. J. 38(2), 73–84 (2004).
[Crossref]

Furuya, K.

K. Furuya, M. Hayashi, Y. Yabushita, and A. Ishikawa, “Phytoplankton dynamics in the East China Sea in spring and summer as revealed by HPLC-derived pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 50(2), 367–387 (2003).
[Crossref]

Geriš, R.

J. Gregor, R. Geriš, B. Maršálek, J. Heteša, and P. Marvan, “In situ quantification of phytoplankton in reservoirs using a submersible spectrofluorometer,” Hydrobiologia 548(1), 141–151 (2005).
[Crossref]

Gikuma-Njuru, P.

R. Alexander, P. Gikuma-Njuru, and J. Imberger, “Identifying spatial structure in phytoplankton communities using multi‐wavelength fluorescence spectral data and principal component analysis,” Limnol. Oceanogr. Methods 10(6), 402–415 (2012).
[Crossref]

Gong, G.-C.

G.-C. Gong, Y.-L. Lee Chen, and K.-K. Liu, “Chemical hydrography and chlorophyll a distribution in the East China Sea in summer: implications in nutrient dynamics,” Cont. Shelf Res. 16(12), 1561–1590 (1996).
[Crossref]

Gregor, J.

J. Gregor, R. Geriš, B. Maršálek, J. Heteša, and P. Marvan, “In situ quantification of phytoplankton in reservoirs using a submersible spectrofluorometer,” Hydrobiologia 548(1), 141–151 (2005).
[Crossref]

Groleau, A.

N. Escoffier, C. Bernard, S. Hamlaoui, A. Groleau, and A. Catherine, “Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state,” J. Plankton Res. 37(1), 233–247 (2015).
[Crossref]

Guinasso, N. L.

J. H. See, L. Campbell, T. L. Richardson, J. L. Pinckney, R. Shen, and N. L. Guinasso, “Combining new technologies for determination of phytoplankton community structure in the Northern Gulf of Mexico 1,” J. Phycol. 41(2), 305–310 (2005).
[Crossref]

Hamlaoui, S.

N. Escoffier, C. Bernard, S. Hamlaoui, A. Groleau, and A. Catherine, “Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state,” J. Plankton Res. 37(1), 233–247 (2015).
[Crossref]

A. Catherine, N. Escoffier, A. Belhocine, A. B. Nasri, S. Hamlaoui, C. Yéprémian, C. Bernard, and M. Troussellier, “On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs,” Water Res. 46(6), 1771–1784 (2012).
[Crossref] [PubMed]

Hansen, U.-P.

M. Beutler, K. H. Wiltshire, B. Meyer, C. Moldaenke, C. Lüring, M. Meyerhöfer, U.-P. Hansen, and H. Dau, “A fluorometric method for the differentiation of algal populations in vivo and in situ,” Photosynth. Res. 72(1), 39–53 (2002).
[Crossref] [PubMed]

Hardman-Mountford, N. J.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
[Crossref]

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Modell. 221(11), 1472–1483 (2010).
[Crossref]

Harrison, J.

J. Harrison, T. E. Howell, S. B. Watson, and R. E. Smith, “Improved estimates of phytoplankton community composition based on in situ spectral fluorescence: use of ordination and field-derived norm spectra for the bbe FluoroProbe,” Can. J. Fish. Aquat. Sci. 73(10), 1472–1482 (2016).
[Crossref]

Hashioka, T.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
[Crossref]

Hayashi, M.

S. Wang, J. Ishizaka, T. Hirawake, Y. Watanabe, Y. Zhu, M. Hayashi, and S. Yoo, “Remote estimation of phytoplankton size fractions using the spectral shape of light absorption,” Opt. Express 23(8), 10301–10318 (2015).
[Crossref] [PubMed]

S. Wang, J. Ishizaka, H. Yamaguchi, S. Tripathy, M. Hayashi, Y. Xu, Y. Mino, T. Matsuno, Y. Watanabe, and S. Yoo, “Influence of the Changjiang River on the light absorption properties of phytoplankton from the East China Sea,” Biogeosciences 11(7), 1759–1773 (2014).
[Crossref]

K. Furuya, M. Hayashi, Y. Yabushita, and A. Ishikawa, “Phytoplankton dynamics in the East China Sea in spring and summer as revealed by HPLC-derived pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 50(2), 367–387 (2003).
[Crossref]

Heteša, J.

J. Gregor, R. Geriš, B. Maršálek, J. Heteša, and P. Marvan, “In situ quantification of phytoplankton in reservoirs using a submersible spectrofluorometer,” Hydrobiologia 548(1), 141–151 (2005).
[Crossref]

Higgins, H.

M. Mackey, D. Mackey, H. Higgins, and S. Wright, “CHEMTAX a program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton,” Mar. Ecol. Prog. Ser. 144, 265–283 (1996).
[Crossref]

Hirata, T.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
[Crossref]

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Modell. 221(11), 1472–1483 (2010).
[Crossref]

Hirawake, T.

Hofmann, H.

H. Hofmann and F. Peeters, “In-situ optical and acoustical measurements of the buoyant cyanobacterium p. Rubescens: spatial and temporal distribution patterns,” PLoS One 8(11), e80913 (2013).
[Crossref] [PubMed]

Horiuchi, T.

M. Yoshida, T. Horiuchi, and Y. Nagasawa, “In situ multi-excitation chlorophyll fluorometer for phytoplankton measurements: Technologies and applications beyond conventional fluorometers,” in Proceedings of the OCEANS (IEEE, 2011), pp. 1–4.

Horne, E.

S. E. Craig, C. T. Jones, W. K. W. Li, G. Lazin, E. Horne, C. Caverhill, and J. J. Cullen, “Deriving optical metrics of coastal phytoplankton biomass from ocean colour,” Remote Sens. Environ. 119, 72–83 (2012).
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Houliez, E.

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S. W. Wright, R. L. van den Enden, I. Pearce, A. T. Davidson, F. J. Scott, and K. J. Westwood, “Phytoplankton community structure and stocks in the Southern Ocean (30–80 E) determined by CHEMTAX analysis of HPLC pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 57(9-10), 758–778 (2010).
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J. H. See, L. Campbell, T. L. Richardson, J. L. Pinckney, R. Shen, and N. L. Guinasso, “Combining new technologies for determination of phytoplankton community structure in the Northern Gulf of Mexico 1,” J. Phycol. 41(2), 305–310 (2005).
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A. Isobe, M. Ando, T. Watanabe, T. Senjyu, S. Sugihara, and A. Manda, “Freshwater and temperature transports through the Tsushima‐Korea Straits,” J. Geophys. Res.: Oceans 107(C7), 3065 (2002).
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Shen, R.

J. H. See, L. Campbell, T. L. Richardson, J. L. Pinckney, R. Shen, and N. L. Guinasso, “Combining new technologies for determination of phytoplankton community structure in the Northern Gulf of Mexico 1,” J. Phycol. 41(2), 305–310 (2005).
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Shen, Z.

M. Zhou, Z. Shen, and R. Yu, “Responses of a coastal phytoplankton community to increased nutrient input from the Changjiang (Yangtze) River,” Cont. Shelf Res. 28(12), 1483–1489 (2008).
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X. Chen, R. Su, Y. Bai, X. Shi, and R. Yang, “Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX,” Acta Oceanol. Sin. 33(12), 192–205 (2014).
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J. Harrison, T. E. Howell, S. B. Watson, and R. E. Smith, “Improved estimates of phytoplankton community composition based on in situ spectral fluorescence: use of ordination and field-derived norm spectra for the bbe FluoroProbe,” Can. J. Fish. Aquat. Sci. 73(10), 1472–1482 (2016).
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H. Yamaguchi, H.-C. Kim, Y. B. Son, S. W. Kim, K. Okamura, Y. Kiyomoto, and J. Ishizaka, “Seasonal and summer interannual variations of SeaWiFS chlorophyll a in the Yellow Sea and East China Sea,” Prog. Oceanogr. 105, 22–29 (2012).
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Z. Li, L. Li, K. Song, and N. Cassar, “Estimation of phytoplankton size fractions based on spectral features of remote sensing ocean color data,” J.Geophys. Res.: Oceans 118(3), 1445–1458 (2013).
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A. Bracher, M. Taylor, B. Taylor, T. Dinter, R. Röttgers, and F. Steinmetz, “Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of phytoplankton pigments concentrations,” Ocean Sci. 11(1), 139–158 (2015).
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X. Chen, R. Su, Y. Bai, X. Shi, and R. Yang, “Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX,” Acta Oceanol. Sin. 33(12), 192–205 (2014).
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A. Isobe, M. Ando, T. Watanabe, T. Senjyu, S. Sugihara, and A. Manda, “Freshwater and temperature transports through the Tsushima‐Korea Straits,” J. Geophys. Res.: Oceans 107(C7), 3065 (2002).
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A. Bracher, M. Taylor, B. Taylor, T. Dinter, R. Röttgers, and F. Steinmetz, “Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of phytoplankton pigments concentrations,” Ocean Sci. 11(1), 139–158 (2015).
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A. Bracher, M. Taylor, B. Taylor, T. Dinter, R. Röttgers, and F. Steinmetz, “Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of phytoplankton pigments concentrations,” Ocean Sci. 11(1), 139–158 (2015).
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D. M. Nelson, P. Tréguer, M. A. Brzezinski, A. Leynaert, and B. Quéguiner, “Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation,” Global Biogeochem. Cycles 9(3), 359–372 (1995).
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L. Van Heukelem and C. S. Thomas, “Computer-assisted high-performance liquid chromatography method development with applications to the isolation and analysis of phytoplankton pigments,” J. Chromatogr. A 910(1), 31–49 (2001).
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J. Harrison, T. E. Howell, S. B. Watson, and R. E. Smith, “Improved estimates of phytoplankton community composition based on in situ spectral fluorescence: use of ordination and field-derived norm spectra for the bbe FluoroProbe,” Can. J. Fish. Aquat. Sci. 73(10), 1472–1482 (2016).
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K. Furuya, M. Hayashi, Y. Yabushita, and A. Ishikawa, “Phytoplankton dynamics in the East China Sea in spring and summer as revealed by HPLC-derived pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 50(2), 367–387 (2003).
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T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8(2), 311–327 (2011).
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X. Chen, R. Su, Y. Bai, X. Shi, and R. Yang, “Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX,” Acta Oceanol. Sin. 33(12), 192–205 (2014).
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A. Catherine, N. Escoffier, A. Belhocine, A. B. Nasri, S. Hamlaoui, C. Yéprémian, C. Bernard, and M. Troussellier, “On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs,” Water Res. 46(6), 1771–1784 (2012).
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S. Wang, J. Ishizaka, T. Hirawake, Y. Watanabe, Y. Zhu, M. Hayashi, and S. Yoo, “Remote estimation of phytoplankton size fractions using the spectral shape of light absorption,” Opt. Express 23(8), 10301–10318 (2015).
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M. Zhou, Z. Shen, and R. Yu, “Responses of a coastal phytoplankton community to increased nutrient input from the Changjiang (Yangtze) River,” Cont. Shelf Res. 28(12), 1483–1489 (2008).
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Z.-Y. Zhu, W.-M. Ng, S.-M. Liu, J. Zhang, J.-C. Chen, and Y. Wu, “Estuarine phytoplankton dynamics and shift of limiting factors: A study in the Changjiang (Yangtze River) Estuary and adjacent area,” Estuar. Coast. Shelf Sci. 84(3), 393–401 (2009).
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M. Zhou, Z. Shen, and R. Yu, “Responses of a coastal phytoplankton community to increased nutrient input from the Changjiang (Yangtze) River,” Cont. Shelf Res. 28(12), 1483–1489 (2008).
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Zhu, Z.-Y.

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Acta Oceanol. Sin. (1)

X. Chen, R. Su, Y. Bai, X. Shi, and R. Yang, “Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX,” Acta Oceanol. Sin. 33(12), 192–205 (2014).
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C.-F. J. Wu, “Jackknife, bootstrap and other resampling methods in regression analysis,” Ann. Stat. 14(4), 1261–1295 (1986).
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S. A. Kring, S. E. Figary, G. L. Boyer, S. B. Watson, and M. R. Twiss, “Rapid in situ measures of phytoplankton communities using the bbe FluoroProbe: evaluation of spectral calibration, instrument intercompatibility, and performance range,” Can. J. Fish. Aquat. Sci. 71(7), 1087–1095 (2014).
[Crossref]

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K. Furuya, M. Hayashi, Y. Yabushita, and A. Ishikawa, “Phytoplankton dynamics in the East China Sea in spring and summer as revealed by HPLC-derived pigment signatures,” Deep Sea Res. Part II Top. Stud. Oceanogr. 50(2), 367–387 (2003).
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S. R. Rogers, T. Webster, W. Livingstone, and N. J. O’Driscoll, “Airborne Laser-Induced Fluorescence (LIF) Light Detection and Ranging (LiDAR) for the Quantification of Dissolved Organic Matter Concentration in Natural Waters,” Estuaries Coasts 35(4), 959–975 (2012).
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Global Biogeochem. Cycles (1)

D. M. Nelson, P. Tréguer, M. A. Brzezinski, A. Leynaert, and B. Quéguiner, “Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation,” Global Biogeochem. Cycles 9(3), 359–372 (1995).
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Z. Li, L. Li, K. Song, and N. Cassar, “Estimation of phytoplankton size fractions based on spectral features of remote sensing ocean color data,” J.Geophys. Res.: Oceans 118(3), 1445–1458 (2013).
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Figures (10)

Fig. 1
Fig. 1

Locations of the sampling stations in the East China Sea (ECS) in 2011 and 2013 and in the Tsushima Strait (TS) in 2012.

Fig. 2
Fig. 2

Comparisons of the HPLC-derived Chl a fractions of brown algae (a), cyanobacteria (b) and green algae (c) with the default output values of the Multi-Exciter. Black lines indicate the 1:1 line, and grey dashes indicate the ± 0.2 fraction range relative to the 1:1 line.

Fig. 3
Fig. 3

Flow chart showing the of model training and estimation procedures.

Fig. 4
Fig. 4

Phytoplankton community derived from HPLC pigments using CHEMTAX program in the East China Sea (a) during the cruises in 2011 and 2013 and in the Tsushima Strait during the 2012 cruise.

Fig. 5
Fig. 5

Characteristics of the fluorescence excitation spectra F(λ) (a), F(λ) normalized by the spectral mean value N_ F(λ) (b), N_ F(λ) dominated by brown algae (c) and N_ F(λ) dominated by cyanobacteria (d)

Fig. 6
Fig. 6

Scatterplots of HPLC-derived Chl a fractions of brown algae (a), cyanobacteria (b), green algae (c) and cryptophytes (d) versus the values derived from the fluorescence excitation spectra F(λ). Black lines indicate the 1:1 line, and grey dashes indicate the ± 0.2 fraction range relative to the 1:1 line.

Fig. 7
Fig. 7

Number of training points versus Jackknife RMSE (RMSE_J) (left axis) and the ratio of RMSE_J to RMSE of the model fitted on the full data set (right axis) for estimating the Chl a fractions of brown algae (a), cyanobacteria (b), green algae (c) and cryptophytes (d).

Fig. 8
Fig. 8

Relative estimation errors of the models for estimating the Chl a fractions of brown algae, cyanobacteria and green algae when 20% random error was added to each band of the fluorescence excitation spectra.

Fig. 9
Fig. 9

Profile distributions of the Chl a fractions of brown algae (a), cyanobacteria (b), green algae (c) and cryptophytes (d) derived from the fluorescence excitation spectra.

Fig. 10
Fig. 10

Scatterplots of the HPLC-derived Chl a fractions of brown algae (a), cyanobacteria (b), green algae (c) and cryptophytes (d) versus the values derived from the fluorescence excitation spectra F(λ) using the models calibrated on the ECS and TS data sets. Black lines indicate the 1:1 line, and grey dashes indicate the ± 0.2 fraction range relative to the 1:1 line.

Tables (2)

Tables Icon

Table 1 Statistics of HPLC-derived Chl a fractions (f) of each phytoplankton group, fluorescence excitation spectra (F(λ)) and normalized F(λ) by the spectral mean value (N_ F(λ)) (N = 141). Max, Min, SD and CV indicate the values of maximum, minimum, standard deviation and coefficient of variation, respectively.

Tables Icon

Table 2 Summary of the performances (RMSE) of the full models calibrated using the full data set, the East China Sea (ECS) models calibrated using the ECS data set and the Tsushima Strait (TS) models calibrated using the TS data set.

Equations (4)

Equations on this page are rendered with MathJax. Learn more.

F(λ)= i=1 m C i N i
F BR ( λ 1 , λ 2 )= F( λ 1 ) F( λ 2 ) , λ 2 > λ 1
F CR ( λ 1 , λ 2 , λ 3 )= F( λ 2 ) F C ( λ 1 , λ 2 , λ 3 ) , λ 3 > λ 2 > λ 1
f= 1 1+exp[( c 0 + i=1 k c i S i )]

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